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The technology industry is facing up to the world-shaking ramifications of artificial intelligence. There is now a recognition that AI will disrupt how societies operate, from education and employment to how data will be collected about people.
科技行业正准备迎接人工智能带来的震撼世界的影响。如今人们意识到，从教育、就业，到如何收集人们的数据，人工智能将扰乱社会运转的方式。
Machine learning, a form of advanced pattern recognition that enables machines to make judgments by analysing large volumes of data, could greatly supplement human thought. But such soaring capabilities have stirred almost Frankenstein-like fears about whether developers can control their creations.
机器学习是一种高级形态的模式识别，能够让机器通过分析大量数据来做出判断。这有望大大辅助人类思维。但这种与日俱增的能力引发了近乎“科学怪人”(Frankenstein)式的担忧：开发人员能否控制他们创造出的机器？
Failures of autonomous systems — like the death last yearof a US motorist in a partially self-driving car from Tesla Motors — have led to a focus on safety, says Stuart Russell, a professor of computer science and AI expert at the University of California, Berkeley. “That kind of event can set back the industry a long way, so there is a very straightforward economic self-interest here,” he says.
加州大学伯克利分校(University of California, Berkeley)计算机科学教授、人工智能专家斯图亚特?拉塞尔(Stuart Russell)表示，自动系统的失误（就像去年驾驶一辆特斯拉汽车(Tesla Motors)部分自动驾驶汽车的美国驾车者死亡那样）促使人们关注安全。他表示：“这种事件可能会严重阻碍行业的发展，因此这里有着非常直接的经济自身利益。”
Alongside immigration and globalisation, fears of AI-driven automation are fuelling public anxiety about inequality and job security. The election of Donald Trump as US president and the UK’s vote to leave the EU were partly driven by such concerns. While some politicians claim protectionist policies will help workers, many industry experts say most jobs losses are caused by technological change, largely automation.
除了移民和全球化，对人工智能驱动的自动化的担忧，正引发公众对于不平等和就业安全的担忧。唐纳德?特朗普(Donald Trump)当选美国总统以及英国投票退出欧盟(EU)在一定程度上就是受到这类担忧的推动。尽管一些政治人士声称，保护主义政策将有利于劳动者，但很多行业专家表示，多数就业损失是由科技变革（主要是自动化）造成的。
Global elites — those with high income and educational levels, who live in capital cities — are considerably more enthusiastic about innovation than the general population, the FT/Qualcomm Essential Future survey found. This gap, unless addressed, will continue to cause political friction.
英国《金融时报》/高通(Qualcomm)联合开展的Essential Future调查发现，全球精英（那些收入和受教育程度高、生活在首都城市的人）对于创新要比普通大众热情得多。除非弥合这种差距，否则它将继续引发政治摩擦。
Vivek Wadhwa, a US-based entrepreneur and academic who writes about ethics and technology, thinks the new wave of automation has geopolitical implications: “Tech companies must accept responsibility for what they’re creating and work with users and policymakers to mitigate the risks and negative impacts. They must have their people spend as much time thinking about what could go wrong as they do hyping products.
美国企业家、撰写道德和科技文章的学者维微克?瓦德瓦(Vivek Wadhwa)认为，新的自动化浪潮具有地缘政治上的潜在影响：“科技公司必须对他们所创造出的东西承担责任，并与用户和政策制定者合作，缓解风险和负面影响。他们必须让员工花时间思考哪里可能出错，就像他们花时间宣传产品那样。”
The industry is bracing itself for a backlash. Advances in AI and robotics have brought automation to areas of white-collar work, such as legal paperwork and analysing financial data. Some 45 per cent of US employees’ work time is spent on tasks that could be automated with existing technologies, a study by McKinsey says.
人工智能行业正在准备应对反弹。人工智能和机器人领域的进步，已经把自动化引入白领工作领域，例如法律文书和分析财务数据。麦肯锡(McKinsey)的一项研究称，在美国员工的工作时间中，大约有45%用在可以借助现有技术实现自动化的任务上。
Industry and academic initiatives have been set up to ensure AI works to help people. These include the Partnership on AI to Benefit People and Society, established by companies including IBM, and a $27m effort involving Harvard and the Massachusetts Institute of Technology. Groups like Open AI, backed by Elon Musk and Google, have made progress, says Prof Russell: “We’ve seen papers?.?.?.?that address the technical problem of safety.”
为了确保人工智能有利于人类，已经建立了一些行业和学术计划。其中包括由IBM等公司创建的人工智能造福人类和社会合作组织(Partnership on AI to Benefit People and Society)，以及涉及哈佛大学(Harvard)和麻省理工学院(MIT)的一项2700万美元计划。得到埃隆?马斯克(Elon Musk)和谷歌(Google)支持的OpenAI等组织已取得进展，拉塞尔教授表示：“我们看到了一些论文……它们针对安全性的技术问题。”
There are echoes of past efforts to deal with the complications of a new technology. Satya Nadella, chief executive of Microsoft, compares it to 15 years ago when Bill Gates rallied his company’s developers to combat computer malware. His “trustworthy computing” initiative was a watershed moment. In an interview with the FT, Mr Nadella said he hoped to do something similar to ensure AI works to benefit humans.
这方面有一些过去应对新技术影响努力的回声。微软(Microsoft)首席执行官萨蒂亚?纳德拉(Satya Nadella)将其与15年前相比，当时比尔?盖茨(Bill Gates)动员公司的开发人员抗击电脑恶意程序。他发起的“可信计算”倡议是一个分水岭。纳德拉在接受英国《金融时报》采访时表示，他希望采取类似的举措以确保人工智能造福于人类。
AI presents some thorny problems, however. Machine learning systems derive insights from large amounts of data. Eric Horvitz, a Microsoft executive, told a US Senate hearing late last year that these data sets may themselves be skewed. “Many of our data sets have been collected?.?.?.?with assumptions we may not deeply understand, and we don’t want our machine-learned applications?.?.?.?to be amplifying cultural biases,” he said.
然而，人工智能带来了一些棘手的问题。机器学习系统从大量数据中得出见解。微软高管埃里克?霍维茨(Eric Horvitz)去年底在美国参议院听证会上表示，这些数据集可能本身就存在问题。他表示：“我们的很多数据集是……在假设我们可能并不深入理解的情况下收集的，我们不希望让我们的机器学习应用……放大文化偏见。”
Last year, an investigation by news organisation ProPublica found that an algorithm used by the US justice system to determine whether criminal defendants were likely to reoffend, had a racial bias. Black defendants with a low risk of reoffending were more likely than white ones to be labelled as high risk.
新闻机构ProPublica去年进行的一项调查发现，美国司法机构用来确定刑事被告人是否有可能再次犯罪的算法存在种族偏见。再次犯罪风险较低的黑人被告比白人被告更容易被标记为高风险。
Greater transparency is one way forward, for example making it clear what information AI systems have used. But the “thought processes” of deep learning systems are not easy to audit.Mr Horvitz says such systems are hard for humans to understand. “We need to understand how to justify [their] decisions and how the thinking is done.”
提高透明度是一条出路，比如明确人工智能系统使用了哪些信息。但深度学习系统的“思维过程”不容易加以审查。霍维茨表示，人类很难理解这种系统。“我们需要理解如何证明（它们的）决策合理，以及这种思考是如何完成的。”
As AI comes to influence more government and business decisions, the ramifications will be widespread. “How do we make sure the machines we ‘train’ don’t perpetuate and amplify the same human biases that plague society?” asks Joi Ito, director of MIT’s Media Lab.
随着人工智能影响更多政府和企业决策，影响将是广泛的。“我们如何确保我们‘培训’的机器不会固化和放大困扰社会的人类偏见？”麻省理工学院媒体实验室主任伊藤穰一(Joi Ito)问道。
Executives like Mr Nadella believe a mixture of government oversight — including, by implication, the regulation of algorithms — and industry action will be the answer. He plans to create an ethics board at Microsoft to deal with any difficult questions thrown up by AI.
纳德拉等高管认为，答案将是结合政府监督（言外之意，这包括对算法的监管）和行业行动。他计划在微软成立一个道德委员会，以处理人工智能带来的任何棘手问题。
He says: “I want?.?.?.?an ethics board that says, ‘If we are going to use AI in the context of anything that is doing prediction, that can actually have societal impact?.?.?.?that it doesn’t come with some bias that’s built in.’”
他说：“我希望有……一个道德委员会，它会这样说，‘如果我们要在任何作出预测、可能具有实际社会影响的场合使用人工智能……那么它不带有内置的一些偏见’。”
Making sure AI systems benefit humans without unintended consequences is difficult. Human society is incapable of defining what it wants, says Prof Russell, so programming machines to maximise the happiness of the greatest number of people is problematic.
确保人工智能在不会带来一些意想不到的后果的情况下造福人类，是很困难的。拉塞尔教授说，人类社会无法界定自身想要什么，因此通过编程让机器为最多数量的人谋求最大幸福是存在问题的。
This is AI’s so-called “control problem”: the risk that smart machines will single-mindedly pursue arbitrary goals even when they are undesirable. “The machine has to allow for uncertainty about what it is the human really wants,” says Prof Russell.
这就是人工智能所谓的“控制问题”：智能机器将一心追逐武断的目标，甚至当这些目标并不可取的时候也是如此。“机器必须考虑到人类真正想要的东西具有不确定性，”拉塞尔教授说。
Ethics committees will not resolve concerns about AI taking jobs, however. Fears of a backlash were apparent at this year’s World Economic Forum in Davos as executives agonised over how to present AI. The common response was to say machines will make many jobs more fulfilling though other jobs could be replaced.
然而，道德委员会无法平息人们对人工智能夺走工作的担忧。在今年的达沃斯世界经济论坛(World Economic Forum)上，对反弹的担忧很明显，高管们对于如何采用人工智能并作出解释十分焦虑。普遍的回应是，声称机器在可能取代一些工作的同时，也将让许多工作更能带来成就感。
The profits from productivity gains for tech companies and their customers could be huge. How those should be distributed will become part of the AI debate. “Whenever someone cuts cost, that means, hopefully, a surplus is being created,” says Mr Nadella. “You can always tax surplus — you can always make sure that surplus gets distributed differently.”
对科技公司和它们的客户而言，生产率提高带来的利益可能是巨大的。如何分配这些利益将成为有关人工智能的辩论的一部分。“每当有人削减了成本，那就意味着有望创造出一些盈余，”纳德拉说，“你总可以对盈余课税——你总可以确保以不同的方式分配这些盈余。”
